|  |  | dense linear algebra, High Performance Computing, polar decomposition, svd, symmetric eigenvalue problem | 
          
                            |  |  | ambit fields, neural inference methods, simulation-based inference, Spatial and spatio-temporal statistics | 
          
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                            |  | David Keyes, Professor, Applied Mathematics and Computational Science | computational science and engineering, High Performance Computing, machine learning, numerical analysis, parellel computing, Partial Differential Equations, quantum computing, scalable solvers, software development, spatial statistics | 
          
                            |  |  | mode-locked lasers, Optical Frequency Comb, photonic integrated circuits, Silicon-based Heterogeneous Integration | 
          
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